Extraction of Spatio-Temporal Data for Social Networks

  • Judith GelernterEmail author
  • Dong Cao
  • Kathleen M. Carley
Part of the Lecture Notes in Social Networks book series (LNSN, volume 6)


It is often possible to understand group change over time through examining social network data in a spatial and temporal context. Providing that context via text analysis requires identifying locations and associating them with people. Our GeoRef algorithm too automatically does this person-to-place mapping. It involves the identification of location, and uses syntactic proximity of words in the text to link location to person’s name. We describe an application using the algorithm based upon data from the Sudan Tribune divided into three periods in 2006 for the Darfur crisis. Contributions of this paper are (1) techniques to mine for location from text (2) techniques to mine for social network edges (associations between location and person), (3) spatio-temporal maps made from mined data, and (4) social network analysis based on mined data.


Social Network Analysis News Article Common Word Entity Recognition Corpus Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Thanks are due to Michael Bigrigg for his insights into the network analysis. This work was supported in part by the Air Force Office of Sponsored Research (MURI: Computational Modeling of Cultural Dimensions in Adversary Organizations, FA9550-05-1-0388), the Army Research Institute W91WAW07C0063, and the Army Research Office ERDC-TEC W911NF0710317. Additional support was provided by the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Air Force Office of Sponsored Research, Army Research Institute, the Army Research Office, or the U.S. government.


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Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • Judith Gelernter
    • 1
    Email author
  • Dong Cao
    • 1
  • Kathleen M. Carley
    • 1
  1. 1.School of Computer ScienceCarnegie-Mellon UniversityPittsburghUSA

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